0.7.7

Backporting fixes:

• Fix frequency metadata bug for lstnet datasets (#1593)
• Add batch_size attribute to MQCNNEstimator and MQRNNEstimator (#1645)
• Fix NegativeBinomial constructor args in NegativeBinomialOutput (torch) (#1651)

0.8.0

New Features

• add dummy estimator for seasonal_naive (#1598)
• Add STL-AR as one more R baseline model (#1568)
• Allow validation data for TabularEstimator. (#1562)
• QRX fixes and added functionality (#1544)
• Extend FileDataset's Parameters to load_datasets (#1538)
• Serde: Allow encoding of functions and methods. (#1519)
• Settings: Enable partial assignment (#1504)
• Settings: Support for nested args in _inject. (#1503)
• Transform.apply (#1494)
• PyTorch implementation of DeepAR (#1460)
• support Min freq for get_seasonality() method (#1459)
• add deep renewal processes for intermittent demand forecasting (#1458)
• Add transform objects for dealing with sparse time series. (#1421)
• spliced binned pareto (#1410)
• Add callbacks mechanism to Trainer class (#1168)

Bug Fixes

• Fix frequency metadata bug for lstnet datasets (#1593)
• Fix single dispatch register for py36 (#1591)
• R fixes for methods that produce point forecasts or prediction intervals directly (#1564)
• Fix computation of OWA (#1557)
• Fixed QRX bug: ".values()" to ".values" (#1552)
• QRX fixes and added functionality (#1544)
• Fix serde issue with some distribution output types, add test (#1543)
• Add item_id to r forecast predictors (#1537)
• fix ProphetPredictor serialization issue (#1535)
• Add constant dummy time features to TFT for yearly data (#1518)
• Settings: Fix partial assignment. (#1516)
• Fix anomaly detection example (#1515)
• Fix Settings._inject to check if it can provide the value. (#1501)
• Change miniver fallback version from unknown to 0.0.0. (#1457)
• Fix get_lags_for_frequency for minute data in DeepVAR (#1455)
• Fix missing import in gluonts.mx.model.GluonEstimator (#1450)
• Fix train-test split data leakage for m4_yearly and wiki-rolling_nips. (#1445)
• fix compatibility for pandas < 1.1 in time_feature/_base.py (#1437)
• fix edge case in iteration based model averaging (#1345)

Breaking Changes

• QRX fixes and added functionality (#1544)
• Transform.apply (#1494)

Other Changes & Improvements

• shallow import for gluonts.mx module (#1592)
• Mark torch distribution inference tests as flaky (#1586)
• Update REFERENCES.md (#1583)
• Delete pytorch_predictor_example.ipynb (#1574)
• Improve tests for R methods (#1567)
• Rename flake8 action step. (#1555)
• Set max_idle_transforms to the length of the dataset (#1546)
• Add datasets from forecastingdata.org (#1542)
• Train invoke with (#1530)
• Consolidate ZeroFeature from DeepState (#1522)
• Fix indentation (#1500)
• Simplify loader.py (#1495)
• adjustments to variable length functionality in batchify (#1442)
• Use miniver for version resolution. (#1434)
• Add docstrings for metrics. (#1422)
• Fixes for MXNet 1.8 (#1403)

0.7.6

Backporting fixes:

• Fix serde issue with some distribution output types, add test (#1543)

0.7.5

Backporting fixes:

• Train invoke with (#1530)
• fix ProphetPredictor serialization issue (#1535)
• Add item_id to r forecast predictors (#1537)
• Serde: Allow encoding of functions and methods. (#1519)
• Disable tests on Windows for PRs, fix other workflows (#1525)

0.7.4

Backporting fixes:

• Fix Settings._inject to check if it can provide the value. (#1501)
• Fix indentation (#1500)
• Fix anomaly detection example (#1515)
• Add constant dummy time features to TFT for yearly data (#1518)

0.7.3

Backporting fixes:

• Fix get_lags_for_frequency for minute data in DeepVAR (#1455)

0.7.2

Backporting fixes:

• Fixes for MXNet 1.8 (#1403)
• Fix train-test split data leakage for m4_yearly and wiki-rolling_nips. (#1445)
• Lock the version for mxnet theme to 0.3.15 (#1451)
• Fix missing import in gluonts.mx.model.GluonEstimator (#1450)

0.6.9

Backporting fixes:

• Fix train-test split data leakage for m4_yearly and wiki-rolling_nips. (#1445)
• Lock the version for mxnet theme to 0.3.15 (#1451)

0.7.1

Backporting fixes:

• fix compatibility for pandas < 1.1 in time_feature/_base.py (#1437)

0.6.8

Backporting fixes:

• fix s3fs ImportError for fsspec by updating the requirement depending on the python version (#1391)
• fix compatibility for pandas < 1.1 in time_feature/_base.py (#1437)